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Name BOTnet_ACAC_2022_train_300K_MD
Extended ID BOTnet_ACAC_2022_train_300K_MD_BatatiaBatznerKovacsMusaelianSimmDrautzOrtnerKozinskyCsanyi__DS_8gqwz5bw1pvq_0
Description 500 decorrelated geometries sampled from 300 K xTB MD run. Acetylacetone dataset generated from a long molecular dynamics simulation at 300 K using a Langevin thermostat at the semi-empirical GFN2-xTB level of theory. Configurations were sampled at an interval of 1 ps and the resulting set of configurations were recomputed with density functional theory using the PBE exchange-correlation functional with D3 dispersion correction and def2-SVP basis set and VeryTightSCF convergence settings using the ORCA electronic structure package.
Authors Ilyes Batatia
Simon Batzner
Dávid Péter Kovács
Albert Musaelian
Gregor N. C. Simm
Ralf Drautz
Christoph Ortner
Boris Kozinsky
Gábor Csányi
DOI 10.60732/e359e8ed

Cite as: Batatia, I., Batzner, S., Kovács, D. P., Musaelian, A., Simm, G. N. C., Drautz, R., Ortner, C., Kozinsky, B., and Csányi, G. "BOTnet ACAC 2022 train 300K MD." ColabFit, 2023.
For other citation formats, see the DataCite Fabrica page for this dataset.
Elements C (33.33%)
H (53.33%)
O (13.33%)
Number of Data Objects 500
Number of Configurations 500
Number of Atoms 7,500
Configuration Sets by Name (None)
Configuration Sets by ID (None)
Data Objects
ColabFit ID DS_8gqwz5bw1pvq_0
Files colabfitspec.json

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